沙盒快照

from langsmith.sandbox import SandboxClient

client = SandboxClient()

snapshot = client.create_snapshot(
    "python",
    docker_image="python:3.12-slim",
    fs_capacity_bytes=1 * 1024**3,  # 1 GiB
)

print(snapshot.id)

import { SandboxClient } from "langsmith/experimental/sandbox";

const client = new SandboxClient();

const snapshot = await client.createSnapshot(
  "python",
  "python:3.12-slim",
  1_073_741_824, // 1 GiB
);

console.log(snapshot.id);

import os

snapshot = client.create_snapshot(
    "internal-python",
    docker_image="registry.example.com/internal/python:3.12",
    fs_capacity_bytes=2 * 1024**3,
    registry_url="https://registry.example.com",
    registry_username="me",
    registry_password=os.environ["REGISTRY_PASSWORD"],
    timeout=600,
)

const snapshot = await client.createSnapshot(
  "internal-python",
  "registry.example.com/internal/python:3.12",
  2_147_483_648,
  {
    registryUrl: "https://registry.example.com",
    registryUsername: "me",
    registryPassword: process.env.REGISTRY_PASSWORD,
    timeout: 600,
  },
);

sb = client.create_sandbox(snapshot_id=base_snapshot_id, name="setup-box")
sb.run("pip install numpy pandas scikit-learn", timeout=180)
sb.write("/opt/config.yaml", "model: gpt-5\n")

# 将当前文件系统捕获为新快照
snapshot = sb.capture_snapshot("ml-ready")
print(snapshot.id, snapshot.source_sandbox_id)

sb.delete()

# 启动预装了这些依赖的新沙盒
with client.sandbox(snapshot_id=snapshot.id) as sb:
    sb.run("python -c 'import numpy; print(numpy.__version__)'")
    assert sb.read("/opt/config.yaml") == b"model: gpt-5\n"

const running = await client.createSandbox(baseSnapshotId, { name: "setup-box" });
await running.run("pip install numpy pandas scikit-learn", { timeout: 180 });
await running.write("/opt/config.yaml", "model: gpt-5\n");

const snapshot = await running.captureSnapshot("ml-ready");
console.log(snapshot.id, snapshot.source_sandbox_id);

await running.delete();

const sandbox = await client.createSandbox(snapshot.id);
try {
  await sandbox.run("python -c 'import numpy; print(numpy.__version__)'");
  const cfg = await sandbox.read("/opt/config.yaml");
  console.log(new TextDecoder().decode(cfg));
} finally {
  await sandbox.delete();
}

snapshot = sb.capture_snapshot("ml-ready-v2", timeout=600)

const snapshot = await sb.captureSnapshot("ml-ready-v2", { timeout: 600 });

# 列出工作区中的所有快照
snapshots = client.list_snapshots()
for s in snapshots:
    print(s.id, s.name, s.status)

# 通过 ID 获取单个快照
snapshot = client.get_snapshot("550e8400-e29b-41d4-a716-446655440000")

# 删除快照（如果任何沙盒仍然引用它，则会失败）
client.delete_snapshot(snapshot.id)

const snapshots = await client.listSnapshots();
for (const s of snapshots) {
  console.log(s.id, s.name, s.status);
}

const snapshot = await client.getSnapshot("550e8400-e29b-41d4-a716-446655440000");

await client.deleteSnapshot(snapshot.id);

sb = client.create_sandbox(snapshot_id=snapshot.id, name="my-vm")
sb.run("echo 'hello' > /tmp/state.txt")

# 停止沙盒——保留磁盘上的文件
sb.stop()

# 稍后：再次启动它（阻塞直到就绪，默认超时=120秒）
sb.start()

result = sb.run("cat /tmp/state.txt")
assert result.stdout.strip() == "hello"

const sb = await client.createSandbox(snapshot.id, { name: "my-vm" });
await sb.run("echo 'hello' > /tmp/state.txt");

await sb.stop();

await sb.start();

const result = await sb.run("cat /tmp/state.txt");
console.log(result.stdout.trim()); // "hello"